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Chlorophyll-a concentrations in water bodies are one of the most important environmental evaluation indicators in monitoring the water environment. Small water bodies include headwater streams, springs, ditches, flushes, small lakes, and ponds, which represent important freshwater resources. However, the relatively narrow and fragmented nature of small water bodies makes it difficult to monitor chlorophyll-a via medium-resolution remote sensing. In the present study, we first fused Gaofen-6 (a new Chinese satellite) images to obtain 2 m resolution images with 8 bands, which was approved as a good data source for Chlorophyll-a monitoring in small water bodies as Sentinel-2. Further, we compared five semi-empirical and four machine learning models to estimate chlorophyll-a concentrations via simulated reflectance using fused Gaofen-6 and Sentinel-2 spectral response function. The results showed that the extreme gradient boosting tree model (one of the machine learning models) is the most accurate. The mean relative error (MRE) was 9.03%, and the root-mean-square error (RMSE) was 4.5 mg/m3 for the Sentinel-2 sensor, while for the fused Gaofen-6 image, MRE was 6.73%, and RMSE was 3.26 mg/m3. Thus, both fused Gaofen-6 and Sentinel-2 could estimate the chlorophyll-a concentrations in small water bodies. Since the fused Gaofen-6 exhibited a higher spatial resolution and Sentinel-2 exhibited a higher temporal resolution.

Small water bodies ranging in size from 1 to 50,000 m2, are numerous, widely distributed, and have various functions in water storage, agriculture, and fisheries. Small water bodies used for agriculture and fisheries are economically significant in China, hence it is important to properly identify and analyze them. In remote sensing technology, water body identification based on band analysis, image classification, and water indices are often designed for large, homogenous water bodies. Traditional water indices are often less accurate for small water bodies, which often contain submerged or floating plants or easily confused with hill shade. Water quality inversion commonly depends on establishing the relationship between the concentration of water constituents and the observed spectral reflectance. However, individual variation in water quality in small water bodies is enormous and often far beyond the range of existing water quality inversion models. In this study, we propose a method for small water body identification and water quality estimation and test its applicability in Wuhan. The kappa coefficient of small water body identification is over 0.95, and the coefficient of determination of the water quality inversion model is over 0.9. Our results show that the method proposed in this study can be employed to accurately monitor the dynamics of small water bodies. Due to the outbreak of the COVID-19 pandemic, the intensity of human activities decreased. As a response, significant changes in the water quality of small water bodies were observed. The results also suggest that the water quality of small water bodies under different production modes (intensive/casual) respond differently in spatial and temporal dimensions to the decrease in human activities. These results illustrate that effective remote sensing monitoring of small water bodies can provide valuable information on water quality.

We synthesize the interconnected impacts of Texas’ water and energy resources and infrastructure including the cascading effects due to Winter Storm Uri. The government’s preparedness, communication, policies, and response as well as storm impacts on vulnerable communities are evaluated using available information and data. Where knowledge gaps exist, we propose potential research to elucidate health, environmental, policy, and economic impacts of the extreme weather event. We expect that recommendations made here — while specific to the situation and outcomes of Winter Storm Uri — will increase Texas’ resilience to other extreme weather events not discussed in this paper. We found that out of 14 million residents who were on boil water notices, those who were served by very small water systems went, on average, a minimum of three days longer without potable water. Available county-level data do not indicate vulnerable communities went longer periods of time without power or water during the event. More resolved data are required to understand who was most heavily impacted at the community or neighborhood level. Gaps in government communication, response, and policy are discussed, including issues with identifying — and securing power to — critical infrastructure and the fact that the state’s Emergency Alert System was not used consistently to update Texans during the crisis. Finally, research recommendations are made to bolster weaknesses discovered during and after the storm including (1) reliable communication strategies, (2) reducing disproportionate impacts to vulnerable communities, (3) human health impacts, (4) increasing water infrastructure resilience, and (5) how climate change could impact infrastructure resilience into the future.

Pekalongan City was still an endemic area of Lymphatic Filariasis (LF). Twice cycles ofMass Drug Administration (MDA) had been implemented, but the Microfi laria rate (Mf rate) wasstill more than 1%. This observational research aimed to study the potential of Culex quinquefasciatusas a vector of LF in Pekalongan City. A Cross-sectional design was chosen as an approach in compilinginformation related to environmental factors and mosquitoes. The population of this research washouses located in Jenggot and Kertoharjo village with thirty-one houses, located around fi lariasiscases, purposively selected as samples. Variables studied in this research were environmental factorsand mosquito vectors. Data collection using observation, and laboratory examination throughmosquito dissection. Data would be analyzed descriptively. This study found that there were 8 Culexquinquefasciatus tested positive L3 fi larial worm (infective rate 4.39%). There were 74.2% of houseshad mosquitoes’ breeding sites around them. The breeding sites were found at domestic waste disposal,drainage in front of the house, and infi ltration well for liquid waste. As much as 86.2% of the breedingsites contained mosquito larvae. This research concluded that Cx. quinquefasciatus was confi rmedpositive fi laria worm thus establish as mosquito vector for Lymphatic Filariasis in Pekalongan City.The breeding sites related to the mosquito development were small water bodies, drainage in front ofand around the house.

The article discusses the methods used in the field experimental filtration work, which allow you to gain knowledge about the filtration properties and water abundance of rocks. The features of the experimental filtration work in the subsoil areas operated by single water intakes are shown. It is noted that these are small water bodies, both in terms of the number of water wells and the amount of actual water withdrawal. The article proposes to use short-term single pumpings as a field research method in the above-mentioned areas, according to the results of which it is possible to substantiate the amount of required water withdrawal and determine the calculated values of the water conductivity coefficient. As an example, the results of pumping are considered, obtained during the implementation of experimental filtration work at three single water intakes located within the Latitude Ob region. The results of the experimental filtration work served as the source material for calculating the reserves of fresh groundwater. Fresh groundwater reserves were calculated and approved for each site in the amount of 499 m3/day for category B.

Basemap and Planet Fusion—derived from PlanetScope imagery—represent the next generation of analysis ready datasets that minimize the effects of the presence of clouds. These datasets have high spatial (3 m) and temporal (daily) resolution, which provides an unprecedented opportunity to improve the monitoring of on-farm reservoirs (OFRs)—small water bodies that store freshwater and play important role in surface hydrology and global irrigation activities. In this study, we assessed the usefulness of both datasets to monitor sub-weekly surface area changes of 340 OFRs in eastern Arkansas, USA, and we evaluated the datasets main differences when used to monitor OFRs. When comparing the OFRs surface area derived from Basemap and Planet Fusion to an independent validation dataset, both datasets had high agreement (r2 ≥ 0.87), and small uncertainties, with a mean absolute percent error (MAPE) between 7.05% and 10.08%. Pairwise surface area comparisons between the two datasets and the PlanetScope imagery showed that 61% of the OFRs had r2 ≥ 0.55, and 70% of the OFRs had MAPE <5%. In general, both datasets can be employed to monitor OFRs sub-weekly surface area changes, and Basemap had higher surface area variability and was more susceptible to the presence of cloud shadows and haze when compared to Planet Fusion, which had a smoother time series with less variability and fewer abrupt changes throughout the year. The uncertainties in surface area classification decreased as the OFRs increased in size. In addition, the surface area time series can have high variability, depending on the OFR environmental conditions (e.g., presence of vegetation inside the OFR). Our findings suggest that both datasets can be used to monitor OFRs sub-weekly, seasonal, and inter-annual surface area changes; therefore, these datasets can help improve freshwater management by allowing better assessment and management of the OFRs.